Optimum Design Research Articles

Mix Design and Field Detection of Large-Particle-Size Graded Crushed Stone Mixtures for Pavement Reconstruction

Large-particle-size graded crushed stone mixtures (LPS-GCSMs) can improve the shortcomings of conventional graded crushed stone, such as low strength, high deformation, and a low modulus of resilience. At present, there is no systematic research on the gradation design and field evaluation of the LPS-GCSMs. In this study, compaction and California bearing ratio (CBR) tests and field construction conditions were combined to design six kinds of gradation of LPS-GCSM, and the optimum gradation was revealed. In order to improve the mechanical properties of LPS-GCSM, 2.5% cement was added to the mixture to prepare a low-content cement-modified LPS-GCSM (LCC-LPS-GCSM) based on the suggested gradation. The mechanical properties of the LCC-LPS-GCSM were investigated through unconfined compression strength (UCS) and compression rebound modulus (CRM) tests. Moreover, the compaction and deflection properties of LPS-GCSM and LCC-LPS-GCSM were examined through the test battery. The results showed that the optimum gradation of LPS-GCSM can be achieved with a combination of aggregate sizes of 20–40 mm, 10–20 mm, 5–10 mm, and 0–5 mm at a ratio of 44:20:10:26. The passing rates of 19 mm and 4.75 mm should be approximately at the median value of the gradation in view of field construction uniformity and a coarse aggregate interlocking effect. The UCS and CRM values of LCC-LPS-GCSM increased rapidly from 0 day to 28 days while they slowed after 28 days, which was similar to those of cement-stabilized materials. The field detection suggested that LPS-GCSM exhibited favorable compaction and that the addition of cement improved the stability of the field compaction of the mixture. Adding a subbase course of LPS-GCSM between the old pavement and the LCC-LPS-GCSM base can lead to more uniform stress on the base. The results of this study provide a reference for the gradation design of LPS-GCSM and optimization of the design indicators.

Optimal design of chevron braced friction damper for mainshock–aftershock vulnerability control

This study proposes the optimum design of chevron braced friction dampers (CBFDs) for the vulnerability control of steel moment–resisting frames (SMRFs) under mainshock-aftershock (MS-AS) sequences. First, the optimum parameters of the CBFD systems installed in the stories of an inelastic SMRF are found through minimizing the maximum damage index of stories averaged over seven scaled earthquake excitations. The uniform distribution of the story damage along the height of the controlled SMRF is adopted as constraint in the optimization procedure. The damage index is calculated based on the Park-Ang damage model which is expressed based on a linear combination of deformation, moment, and absorbed hysteretic energy of structural elements imposed by an earthquake excitation. Results reveal that the optimized CBFDs-equipped SMRF exhibits better distribution of the story damage than that of the uncontrolled SMRF. Finally, the vulnerability assessment of the optimized CBFDs-equipped SMRF under MS and MS-AS ground motions is investigated by the fragility curves. The fragility assessment emphasize that the optimized CBFDs effectively mitigate the seismic vulnerability of the controlled SMRF under MS-AS sequences at different damage states.

Parametric Optimization of System Modes for Nozzle Turbine Vane by Means of Costimulated Artificial Immune System

One requirement posed by customers is to achieve adequate durability levels as described in technical requirement documents. Modal analysis is one of the design assessments aimed at identifying the risks of high cycle fatigue (HCF). This article presents a novel application of an artificial immune system (AIS) in the optimization of a nozzle guide vane’s modal characteristics. The aim is to optimize the system’s natural frequencies in the vibration vane and adjacent hardware (turbine casing). The geometrical characteristics accounted for in the optimization process include the shell thicknesses on the turbine casing side and the nozzle outer band features (hook thickness, leaning and position). The optimization process is based on a representative model established from FEM analysis results. The framework is robust because of the applied metamodel and does not require time-consuming FEM analysis in order to evaluate the fitness function. The aim is to minimize the model area (a derivative of the system weight) with constraints imposed on the frequency (a penalty function). The optimum design is given as the solution with an increased shell thickness in the turbine casing and leaning nozzle outer band hooks to obtain the maximum stiffness of the system. The results obtained by means of the artificial immune system (AIS) and a novel variant based on an additional costimulation procedure (CAIS) are compared with the solution obtained by means of a genetic algorithm implemented in the commercial CAE software (Ansys version 19.2).

Parasitic-Based Model for Characterizing False Turn-On and Switching-Based Voltage Oscillation in Hybrid T-Type Converter

High frequency and high voltage switching converters utilizing wide bandgap semiconductors are gaining popularity thanks to their compactness and improved efficiency. However, the faster switching requirements gives rise to new challenges. A key issue is the increased oscillation of the drain–source voltage caused by the switching action of the complementary switch in the same phase or change of state of the other phase switches. The voltage stress caused by these oscillations can damage the switch. Furthermore, the high dv/dt during turning-on of one switch might result in false turn-on of the complementary switch due to the miller effect. In this paper, these issues are investigated in a T-type converter through analytical and experimental analysis. Based on the proposed analytical approach, simple and cost-wise solutions utilizing an optimum design of gate driver circuits and circuit layout modifications can be developed to cope with the aforementioned issues. A comprehensive analytical model of the converter with consideration of parasitic capacitances and inductances is developed. By performing sensitivity analysis on the model, the effect of the parasitic parameters on the drain–source voltage oscillation and gate–source voltage amplitude in case of false turn-on is studied. The validity of the model is then assessed through numerical simulations and experimental results.

Local entropy generation optimization and thermodynamic irreversibility analysis of oval-shaped coaxial ground heat exchangers: A detailed numerical investigation

Optimizing the heat transfer and thermodynamic efficiency of Ground Heat Exchangers (GHE) is crucial for maximizing the energy efficiency of Ground-coupled Heat Pump (GCHP) systems utilized in building heating and cooling applications. This study pioneers an effective approach of both the first and second laws of thermodynamics of the newly oval-shaped coaxial GHEs (oval-CGHEs), assessing heat transfer, thermohydraulic performance, and local entropy generation rate to explore the optimum design and operational conditions for heat exchange maximization and entropy generation minimization. Utilizing a three-dimensional numerical model validated by experimental results, this study examines the trade-offs between heat transfer improvements and entropy generation rate intensification of the oval-CGHEs in comparison to the typical circular-shaped CGHE (circle-CGHE) further than exploring the effect of key operational and design parameters and performing sensitivity analysis. The results reveal that oval-CGHEs exhibit higher irreversibility as a penalty for their superior heat transfer capabilities compared to traditional circular-shaped CGHEs (circle-CGHE), which can be mitigated by optimizing the position of the inner tube. Moreover, the study underscores the criticality of maintaining a balance between enhanced heat transfer and the associated rise in irreversibility, particularly concerning the factors of mass flow rates and installation depths.

Abstract PO3-06-09: A phase II study of nivolumab plus ipilimumab and androgen receptor antagonist bicalutamide to stimulate thymic T cell generation in HER2-negative metastatic breast cancer

Abstract Background: Systemic chemotherapy is used commonly in breast cancer and is associated with lymphopenia, potentially limiting efficacy of immune checkpoint blockade. The androgen receptor (AR) serves as a negative regulator of thymic function. AR antagonists, such as bicalutamide, may stimulate thymic production of naïve T-cells, which may help to restore lymphocyte diversity and augment immunotherapy response. The AR is expressed in 50% of hormone receptor negative (HR-) metastatic breast cancer (MBC) and >75% of HR+ MBC, and bicalutamide is clinically active with stable disease as best response. We hypothesize that bicalutamide could be combined with dual immune checkpoint blockade (anti-programmed death 1, nivolumab; plus anti-cytotoxic T-lymphocyte antigen 4, ipilimumab), stimulating T-cell production and resulting in durable clinical response. Methods: This is a phase II Simon 2-stage trial of nivolumab (240 mg IV q2w), ipilimumab (1 mg/kg IV q6w), and bicalutamide (150mg oral daily) for first- or second-line treatment of HER2-negative MBC (NCT03650894). The primary endpoint is iRECIST 24-week clinical benefit rate (CBR), evaluated separately for HR+ MBC (n=15) and AR+/HR- MBC (n=15). An optimum Simon 2-stage design (80% power, 5% one-sided alpha) is employed to evaluate an alternative hypothesis of >50% CBR compared to historical control of < 30% CBR for conventional chemotherapy, with expansion of each cohort planned if ≥6/15 responses are observed. Secondary outcomes include best overall objective response rate (ORR), progression-free and overall survival (PFS,OS), and safety. Exploratory endpoints include assessment of peripheral T-cell counts and T cell receptor excision circles (TREC PCR, Mayo Laboratories, a surrogate of thymic T-cell production) over time. Results: Durable responses were observed, with an ongoing complete response at 41+ months in a patient who discontinued due to toxicity (AR+/HR- cohort, PD-L1 CPS score 3%). Therapy was tolerated with a toxicity profile consistent with prior studies of ipilimumab & nivolumab, with five subjects (19%) requiring treatment discontinuation related to toxicity. Outcomes by cohort and PDL1 are summarized in Table 1. Using mixed effects linear models, therapy was associated with a significant expansion of CD8+ T cells (23/mcL/month, p< .01) but not CD3+ T cells (7/mcL/month, p=.59) or CD4+ T cells (4/mcL/month, p=.65). Baseline TREC counts were higher in younger participants (mean: < 50y 2156/mcL; 50-65y 961/mcL; >65y 311/mcL). TRECs did not increase globally, however TREC expansions were observed in several younger participants. Conclusions: The regimen of ipilimumab, nivolumab, plus bicalutamide is safe and clinically active in 1st/2nd-line HER2-negative MBC. Neither cohort crossed the Simon futility barrier for cohort expansion, however durable responses were observed including in PD-L1-negative patients, highlighting the unmet need for biomarkers to identify candidates for chemotherapy-sparing checkpoint blockade. Further research is indicated to evaluate the impact of AR antagonists on T-cell function and thymic stimulation in MBC. Acknowledgements: Drug and study support was provided by Bristol-Myers Squibb and The BMS International Immuno-Oncology Network (II-ON). Clinical outcomes XX XX HR: hormone receptor; AR: androgen receptor; CPS: PD-L1 combined positive score Citation Format: David Page, Alexander Hall, Krystle Collins, Nicole Moxon, Staci Mellinger, Tracy Kelly, Aysha Kelley, Nicole Fredrich, Amanda Seino, Gabriella Liberatore, Alison Conlin, Zheng Topp, Kelly Perlewitz, Sasha Stanton, Walter Urba, Yaping Wu, Maritza Martel, Zhaoyu Sun, Yoshinobu Kogushi, William Redmond, Tiffany Traina, Ayca Guculp. A phase II study of nivolumab plus ipilimumab and androgen receptor antagonist bicalutamide to stimulate thymic T cell generation in HER2-negative metastatic breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-06-09.

A generalized Benders decomposition approach for the optimal design of a local multi-energy system

A local multi-energy system (LMES) is a decentralized energy system producing energy under multiple forms to satisfy the energy demand of a set of buildings located in its neighborhood. We study the problem of optimally designing an LMES over a multi-phase horizon. This problem is formulated as a large-size mixed-integer linear program with a block-decomposable structure involving mixed-integer sub-problems. We propose a new way to adapt a recently published framework for generalized Benders decomposition to our problem. This is done by exploiting the fact that the constraint matrix appearing in front of the first-stage variables in the coupling constraints is non-negative. The obtained generalized Benders decomposition algorithm relies on the use of a new type of non-convex Benders cuts involving indicator functions. We first prove that, under the assumption that all first-stage decision variables are integer and bounded, the finite and optimal convergence of our algorithm is guaranteed in theory. We then investigate how to obtain a good numerical performance in practice. Finally, we report the results of a computational study carried out on a real-life case study. These results show that the proposed algorithm clearly outperforms both a mathematical programming solver directly solving the problem as a whole and a state-of-the art hierarchical decomposition algorithm.

Time stability of soil volumetric water content and its optimal sampling design in contrasting forest catchments

Characterizing the temporal variation across a forest catchment soil volumetric water content (VWC) with different environmental conditions at different depths for different seasons requires a robust point-scale sampling strategy that balances monitoring cost with predicting accuracy. In the study, the most time-stable locations (MTSLs) using the time-stable concept and the minimum number of required samples (NRS) based on random selection method were studied to explore the optimal sampling design for catchment-mean VWC with an acceptable error (the relative bias (RBIAS) less than 10 %). VWC monitoring was conducted at approximately 25 plots throughout the year in five forest catchments with varying areas and VWC status. Results revealed that the number of MTSLs for mean-VWC estimation with RBIAS within 10 % was directly related to the spatial variability of VWC. Specifically, one MTSL was feasible for accurately estimating mean VWC at different depths in high-VWC catchments with area around or less than 100 ha; one MTSL was adequate for each depth in the catchment with moderate-level VWC; whereas more than one MTSL were necessary for each depth in low-VWC catchment with a larger are of 1800 ha. To identify the MTSL for each catchment, the location with mean VWC was typically situated at the mid-elevation or soil apparent electrical conductivity (ECa) at a certain spatial scale. The NRS for catchment-mean VWC could be determined based on the combination of VWC status, its temporal stability, and potential catchment size, and could be ranked based on the spatial variation of each catchment. If the MTSL cannot be guaranteed for a catchment, the NRS might be a better alternative for optimum sampling design. These finding could be useful in providing guidelines for optimizing VWC monitoring in forest catchments by sampling at a few selected locations representative of the catchment-scale behavior.

Benchmark problems in optimum structural design of 3D reinforced concrete frames

Benchmark problems in optimum structural design of 3D reinforced concrete frames

Optimization of a non-pneumatic tire using design of experiments and machine learning techniques

In this paper, the spoke structure of a non-pneumatic tire is optimized. The finite element model of the spoke structure is created and structural dynamic analysis is made using ABAQUS. The optimization goal is to simultaneously reduce three characteristics of the spoke structure, the mass, vertical displacement and acceleration. Simulations are performed according to the center composite design table, and the objective function is estimated using response surface analysis (RSA), random forest regression (RFR), gradient boosting regression (GBR) and artificial neural network (ANN). The genetic algorithm is used for minimization, and the optimization results of each objective function are analyzed through verification simulation. As a result of the optimization, the error between the predicted value and the actual value is 18.6% for RSA 3.1% for RFR, 1.7% for GBR, and 15.0% for the ANN. The ANN proposes the optimum design variables which derive output values smaller than the current minimum value because the ANN properly represents the nonlinear characteristics of the spoke model generated in this study. Highlights Simulation based optimization of the spoke structure of a non-pneumatic tire Various regression models are used and their accuracy is compared A two-step genetic algorithm is used for optimization

Performance analysis of a novel air source ammonia/water cascade heat pump for heating buildings in subarctic climate

Performance of available air-source heat pumps (ASHP) for buildings is extremely influenced by the outdoor air temperature (OAT). When OAT falls below –20°C, especially in subarctic climate, most commercially available ASHPs lose their defined functionality. To address this issue, a novel cascade heat pump (CHP) is proposed that utilizes two natural (with zero global warming index) refrigerants: ammonia, aka R717, as the low stage (LS) refrigerant, and water, aka R718, as the high stage (HS) working fluid. The proposed system is equipped with two rotary vane compressors for LS and HS. To desuperheat the compressor discharge temperatures and increase the HS heating capacity, liquid refrigerant is injected into the chamber of both LS and HS compressors. The wet compression is thermodynamically modeled and validated against experimental data available in the literature. Optimum design parameters such as the maximum allowable temperatures during compression and the minimum vapor quality after injection are obtained where the COP is maximized. Total exergy destruction, number/location of injectors and the injected amounts are also investigated. The proposed CHP can deliver 6.35 kW heating load at 50°C with a COP of 1.985 when OAT is –40°C. From a broader perspective, the proposed CHP not only proves its efficacy in extremely cold subarctic climates but also emerges as a pivotal player in addressing the global warming issue. This is accomplished through a dual approach to decarbonization—firstly, by electrifying heating processes and secondly, by substituting phased-out refrigerants with environmentally friendly natural alternatives.

Optimizing Integrated Water and Electrical Networks through a Holistic Water–Energy Nexus Approach

As water and electrical networks cannot be entirely independent, a more integrated approach, the water–energy nexus (WEN), is developed. A WEN is the basis of a smart city where water and electrical networks are interconnected and integrated by implementing efficient management strategies. Accordingly, this study develops a dynamic co-optimization model for designing and operating an integrated power and water system. The proposed co-optimization model minimizes the total annual and operational costs of a micro-WEN system while capturing its optimum design values and operating conditions and meeting the demands of the electrical and water networks. Furthermore, this work presents a plan for transitioning from thermal desalination to reverse osmosis (RO) desalination in the United Arab Emirates (UAE). The key objective is to decouple electricity and water production, effectively tackling the issue of operating the UAE’s power plants at low efficiency during the winter while ensuring an adequate water supply to meet the growing demand. The results show that the co-optimization model provides a significant reduction in the total operational cost with the integration of photovoltaic energy and shifting to RO. Most importantly, the micro-WEN system is optimized over multiple timescales to reduce the computation effort and memory requirements.

Development and validation of sloped ground pressure prediction model for a tracked tractor in hilly and mountainous environments

Tracked tractors are better suited for agricultural production in hilly environments because of their excellent stability and flotation. The ground pressure in these environments is highly irregular owing to the ground slope, which has led to a lack of theoretical foundation and data support for the development of hillside tracked tractors (HTTs). Therefore, accurate prediction of the ground pressure at the track-soil interface on inclined terrain is important. In this study, sloped ground pressure prediction model composed of sloped terrain soil pressure-sinkage model was developed to analyse the distribution characteristics of the ground pressure of tracked tractors in agricultural operations on hillside slopes. Considering the influence of the slope angle, soil conditions, operating conditions, and important parameters of the tracked tractors (including mass, centre of gravity, and track gauge), the ground pressure prediction model used harmonic oscillator functions and peak-valley control primitive functions. To validate the proposed model, ground pressure tests of the experimental tracked tractor were conducted at different slope angles and operating conditions in an experimental platform integrating a "soil-machine-crop" system. The results showed that the maximum error between the predicted results and the test data under various slopes and operating conditions was approximately 6.3%, with an average error of approximately 4.7%; the consistency between the test results and the simulated results indicate that the model established in this study is accurate and credible. Based on the ground pressure model, the developed tractive performance prediction model for HTTs had high prediction accuracy for the slip rate and traction force in the climbing traction test. The developed theoretical model and results provide practical guidance for the structural design of advanced HTTs and manoeuvrability optimization.

Novel Detector Configurations in Cone-Beam CT Systems: A Simulation Study

Cone-beam computed tomography (CBCT) has emerged in recent years as an adequate alternative to mammography and tomosynthesis due to the several advantages over traditional mammography, including its ability to provide 3D images, its reduced radiation dose, and its ability to image dense breasts more effectively and conduct more effective breast compressions, etc. Furthermore, CBCT is capable of providing images with high sensitivity and specificity, allowing a more accurate evaluation, even of dense breasts, where mammography and tomosynthesis may lead to a false diagnosis. Clinical and experimental CBCT systems rely on cesium iodine (CsI:Tl) scintillators for X-ray energy conversion. This study comprises an investigation among different novel CBCT detector technologies, consisting either of scintillators (BGO, LSO:Ce, LYSO:Ce, LuAG:Ce, CaF2:Eu, LaBr3:Ce) or semiconductors (Silicon, CZT) in order to define the optimum detector design for a future experimental setup, dedicated to breast imaging. For this purpose, a micro-CBCT system was adapted, using GATE v9.2.1, consisting of the aforementioned various detection schemes. Two phantom configurations were selected: (a) an aluminum capillary positioned at the center of the field of view in order to calculate the system’s spatial resolution and (b) a breast phantom consisting of spheres of different materials, such that their characteristics are close to the breast composition. Breast phantom contrast-to-noise ratios (CNRs) were extracted from the phantom’s tomographic images. The images were reconstructed with filtered back projection (FBP) and ordered subsets expectation-maximization (OSEM) algorithms. The semiconductors acted satisfactorily in low-density matter, while LYSO:Ce, LaBr3:Ce, and LuAG:Ce presented adequate CNRs for all the different spheres’ densities. The energy converters that are presented in this study were evaluated for their performance against the standard CsI:Tl crystal.

Sensitivity analysis of natural convection in a porous cavity filled with nanofluid and equipped with horizontal fins using various optimization methods and MRT-LB

In the present study, natural convection heat transfer is investigated in a porous cavity filled with Cu/water nanofluid and equipped with horizontal fins. Optimization and sensitivity analysis of the fin’s geometry, porous medium and nanofluid properties to maximize heat transfer rate is the aim of this work. To achieve this purpose, a design space is created by input parameters which include length, number of fins, distance between fins, porosity, Darcy number and volumetric fraction of the nanoparticles. Several tools have been used to implement optimization methods including the Taguchi method (TM) for design points generation, sensitivity analysis of design variables by using signal-to-noise ratio (SNR) and analysis of variance (ANOVA), response surface method (RSM) for interpolation and regression by using nonparametric regression, and genetic algorithm (GA) for finding optimum design point. The double multi-relaxation time lattice Boltzmann method (MRT-LBM) is used to analyze and simulate the flow field and heat transfer in each design point. The results show that the optimal configuration leads to an average Nusselt number of 5.56. This optimal configuration is at the length of fins L/2, the number of fins 2, the distance between fins L/12, porosity 0.8, Darcy number 0.1, and the volumetric fraction of the nanoparticles 0.02. By using the SNR results, the Darcy number and the number of fins have the most and the least effect in maximizing the average Nusselt number, respectively. The ANOVA results and global sensitivity analysis (GSA) findings further validated this conclusion.

Performance uniformity analysis in polymer electrolyte fuel cell using long-term dynamic simulation

The temporal stability and spatial homogeneity of current density are key factors in Polymer Electrolyte Fuel Cell (PEFC) performance and durability. Temporal and spatial variations of relative humidity, fuel concentration, and water droplets in the channels are the principal causes of non-homogeneous current density. A dynamic pseudo-3D model was previously proposed by the authors and has been extended and improved to perform the long-term and intensive simulations of PEFC with low computational cost, which allows to study of the performances homogeneity with different experimental configurations and flow field topologies. The model considers important phenomena in the homogeneity analysis, such as gases and liquid water movement in diffusion layers and flow field, electrochemical reactions, and others. Model validation has been performed using experimental data obtained from a 25 cm2 cell with a single serpentine, which has allowed studying the model transient response and spatial representation. The simulations have been used to study the homogeneity and stability of 36 setups of PEFC, varying the rib/channel width ratio, the stoichiometric ratio, and the number of parallel serpentine channels. The results show the importance of a properly flow field design to control gas flow, remove the channels’ liquid water, and keep a homogeneous feeding. The study evaluated a set of channel configurations that show the improved temporal voltage stability and current density spatial homogeneity. The results show the impact of channel gas speed and ratio channel/rib width in liquid droplets removal and the proper fuel spatial distribution; and how configurations with a lesser number of channels in serpentine design require a lower stoichiometric ratio to perform better temporal and spatial uniformity. In the case of the cell configurations simulated, the optimum design was achieved using between 5 and 7 parallel serpentine channels and a channel/rib ratio 3/5.

Surrogate Model Development for Air Foil Thrust Bearings With Chevron-Patterned Trailing Edge

Abstract Air foil thrust bearings provide some advantages over oil-lubricated thrust bearings. The use of these bearings reduces weight and increases dynamic stability, making it possible to reach high rotational speeds. However, as the bearing reaches high rotational speeds, the higher amount of heat generated results in reduced efficiency, deterioration, and even failure of the rotating machinery system. To overcome this, better thermal management is needed for air foil thrust bearings. Addressing this challenge, this study proposes the use of a chevron pattern at the trailing edge of the top foil to enhance air stream mixing, thus influencing heat dissipation. The main purpose of this study is to identify the optimal design parameters of the top foil trailing edge shape and provide a guideline for future air foil thrust bearing design. In this regard, 3D computational fluid dynamics (CFD) simulations are conducted to evaluate an air thrust foil bearing model performance. The highest temperature value occurring in the fluid and load-carrying capacity is selected as the output to find optimum design values. The design of experiments (DOE) technique is utilized for generating the sample points. A surrogate model is then used jointly with a multi-objective optimization to minimize the peak temperature in the air film and increase the load-carrying capacity. The optimal configuration is compared with the baseline, which is also used to validate the computational model with experimental data. This optimal design approach using a surrogate model can be used for further studies on improving the efficiency of air foil thrust bearings.

Research on mix design and mechanical performances of MK-GGBFS based geopolymer pastes using central composite design method

In order to alleviate environmental problems and reduce CO2 emissions, geopolymers had drew attention as a kind of alkali-activated materials. Geopolymers are easier access to raw materials, green and environment friendly than traditional cement industry. Its special reaction mechanism and gel structure show excellent characteristics such as quick hardening, high strength, acid and alkali resistance. In this paper, geopolymer pastes were made with metakaolin (MK) and ground granulated blast furnace slag (GGBFS) as precursors. The effects of liquid–solid ratio (L/S) and modulus of sodium silicate (Ms) on the performances of MK-GGBFS based geopolymer paste (MSGP) were characterized by workability, strength and microstructural tests. The regression equations were obtained by central composite design method to optimize the mix design of MSGP. The goodness of fit of all the equations were more than 98%. Based on the results of experiments, the optimum mix design was found to have L/S of 0.75 and Ms of 1.55. The workability of MSGP was significantly improved while maintaining the strength under the optimum mix design. The initial setting time of MSGP decreased by 71.8%, while both of the fluidity and 28-d compressive strength increased by 15.3%, compared with ordinary Portland cement pastes. Therefore, geopolymers are promising alternative cementitious material, which can consume a large amount of MK and GGBFS and promote green and clean production.

Influence of Shale Mineral Composition and Proppant Filling Patterns on Stress Sensitivity in Shale Reservoirs

Shale reservoirs typically exhibit high density, necessitating the use of horizontal wells and hydraulic fracturing techniques for efficient extraction. Proppants are commonly employed in hydraulic fracturing to prevent crack closure. However, limited research has been conducted on the impact of shale mineral composition and proppant filling patterns on shale stress sensitivity. In this study, shale cylindrical core samples from two different lithologies in Jimusaer, Xinjiang in China were selected. The mineral composition and microscopic structures were tested, and a self-designed stress sensitivity testing system was employed to conduct stress sensitivity tests on natural cores and fractured cores with different proppant filling patterns. The experimental results indicate that the stress sensitivity of natural shale porous cores is weaker, with a stress sensitivity coefficient below 0.03, significantly lower than that of fractured cores. The shale mineral composition has a significant impact on stress sensitivity, with the stress sensitivity of clayey argillaceous shale cores, characterized by higher clay mineral content, being higher than that of sandy argillaceous shale, characterized by higher quartz mineral content. This pattern is also applicable to fractured cores filled with proppants, but the difference gradually diminishes with increased proppant concentration. The choice of large particles and high-concentration proppant bedding can enhance crack conductivity. Within the experimental range, the crack conductivity of 20–40 mesh quartz sand is more than three times that of 70–120 mesh quartz sand. At an effective stress of 60 MPa, the conductivity of cores with a proppant concentration of 2 kg/m2 is 3.61 times that of cores with a proppant concentration of 0.3 kg/m2. Under different particle size combinations of proppant filling patterns, the crack conductivity at the crack front with large-particle proppants is 6.21 times that of mixed bedding. This study provides valuable insights for the hydraulic fracturing design of shale reservoirs and optimization of production system parameters in subsequent stages.

Neutronic Analysis of the Conceptual Molten Uranium Breeder Reactor Using MCNP and SCALE Tools

The Molten Uranium Breeder Reactor (MUBR) is a radically new reactor concept with a mixed-energy spectrum. MUBR is fueled with molten uranium metal in large-diameter fuel tubes and is cooled by circulating molten uranium fuel through a heat exchanger. The reactor has heavy water as moderator, and the reactivity of the reactor is primarily controlled by the voiding effect of the moderator through an innovative control cavity structure design. Because the MUBR design is vastly different from most existing fission reactors, neutronics analysis must be performed for many different combinations of design parameters to identify viable and optimum design configurations. To facilitate the neutronics analysis, a proprietary program called MUBR6gen is being developed to provide a pipeline tool to expedite the process. MUBR6gen employs two well-established neutronics codes, i.e., MCNP and SCALE, to perform standard neutronics calculations for MUBR by automating input preparation and output processing. In addition, MUBR6gen ensures consistency of the MCNP and SCALE inputs and compares the outputs of the two codes to warrant the simulation results. Augmented with MUBR6gen, standard neutronics analysis was carried out on a small-scale MUBR design, which serves as a model problem in the paper. The neutronics performance characteristics of the model reactor were obtained and discussed in a code-to-code pattern. An overall very good agreement between the results of the two neutronics codes was established. Based on the success of the model problem analysis, further neutronics analysis using MUBR6gen was extended for a set of MUBR variant designs. Meaningful and promising fuel cycle analysis results for the 10 different designs were achieved and discussed. These results are used to identify the best MUBR candidates in terms of fuel lifetime and utilization efficiency for future applications.